Bringing the right context to the models is actually a very hard problem. But luckily for us, like you know, that's the thing that we we've been working on for the last six to seven years. Like our whole like the the model for Glean has always been go deep, you know, connect with all the enterprise systems and now start to build an understanding of how this business actually works.Yeah. >> Understand like you know the data, the knowledge, understand business processes work and like you know given any task l ...

Bret Taylor is the CEO of Sierra and chair of OpenAI's board. Taylor joins Big Technology Podcast to discuss how AI is reshaping software, from vibe coding to the rise of AI agents that will replace dashboards, forms, and the way we interact with technology. We also cover OpenAI's decision to introduce ads, whether AI progress is actually slowing down, and what Brett has learned from working with Sam Altman, Mark Zuckerberg, Elon Musk, and Sheryl Sandberg. Hit play for an essential conversation on the futur ...

Token Narratives of 20251. Memecoins2. Artificial Intelligence (AI)3. Real-World Assets (RWA)4. AI Agents5. Made-in-USA Tokens6. Solana Memecoins7. Layer 1s8. Decentralized Finance (DeFi)9. Base Ecosystem10. DeFAIWhat are you betting on this 2026? ...

Core Insights - The article discusses how China's 15th Five-Year Plan will influence its industrial landscape, particularly focusing on AI and semiconductors as national priorities [1][5]. AI and Semiconductor Industry - AI is being integrated with manufacturing and energy systems, emphasizing the development of industry-specific large models rather than being treated as a standalone growth sector [6]. - Demand for computing power has shifted from being a discretionary choice to a foundational demand, benefiting sectors like optical communications, where companies like Zhongji Innolight and Eoptolink Technology have seen share price increases of 389.7% and 320% respectively over the past year [7][8]. - In semiconductors, the focus has shifted from comprehensive substitution to deployable capabilities, with SMIC's shares rising about 80% over the past year due to demand for mature-node processes and automotive chips [8][9]. AI Platforms and Market Dynamics - The competition in AI large models is transitioning from startups to major internet platforms, with Baidu and Alibaba facing investor skepticism despite their technological visibility [11][12]. - Tencent has shown stable market performance by embedding AI across its services, resulting in a share price increase of over 50% in the past year, indicating a preference for AI narratives that enhance cash flow quality [13]. Emergence of AI Agents - AI agents are evolving from general-purpose models to specific applications, marking a shift towards embedding AI in real-world workflows, as seen with ByteDance's Doubao [14][15]. - The U.S. tech giants focus on frontier model capabilities, while China emphasizes rapid deployment and monetization of AI technologies [16][17]. Robotics and Power Systems - Robotics is increasingly adopting a Robotics-as-a-Service (RaaS) model, which lowers adoption barriers for enterprises, with global installations of humanoid robots expected to reach approximately 16,000 units by 2025 [19][20]. - Companies like Ubtech have seen stock price increases of over 135% in the past year, while other industrial automation firms have also experienced gains of around 30% [21]. - Power and energy systems are being re-evaluated, with a focus on stability and efficiency, leading to a resurgence in interest for power electronics and energy storage companies [23][24]. - Share prices for companies like Sungrow Power Supply have more than doubled, reflecting a recovery in demand for energy storage solutions [24][25].

If larger markets are going to mirror crypto markets in the future and everything's going to be 247 trading, 24-hour trading, 7 days a week, always on, never off, it it now becomes a just a reality that you're going to have to get your hands on tools [music] that are there for you while you sleep. your ability to affect transactions without emotion [music] and to not get beat uh by institutional algorithms. You have to get your hands on it and that's where we're headed.What's going on guys. Today we've got ...

As you uh develop more and more agents, as you take u these human-driven processes and agentify them, you have to think about like how do you bring that full comprehensive enterprise context to all all of these different agents. And ideally, we feel like AI should be like electricity. It just disappear.We don't, you know, be using AI without even knowing using AI. And it's almost like augumented reality before work. Arvin Ping, thank you so much for joining us for Greylock Change Agents.As you know, change ...

If you're building aic apps, you probably already have the basics working. A chat UX that streams the response to the front end and maybe a tool call or two. But here's the thing.Most of the agent demos still feel like demos. And the gap between a demo and something that feels production ready is usually not a huge rewrite. It's a few features that are often hidden in plain sight.That's why in this video, we're going to talk about three less known longchain features that once you know them will make your Ge ...

Core Insights - North American cloud service providers (CSPs) are significantly increasing investments in AI infrastructure, leading to a projected annual growth rate of over 28% in global AI server shipments by 2026 [1] - The demand for AI inference services is driving a replacement and expansion cycle for general servers, with an expected annual growth rate of 12.8% in global server shipments (including AI servers) by 2026 [1] Group 1: Market Trends - From 2024 to 2025, the server market will focus on training advanced large language models (LLMs) using AI servers equipped with GPUs and HBM for parallel computing [3] - Starting in the second half of 2025, the development of AI inference services such as AI Agents, LLaMA model applications, and Copilot upgrades will prompt CSPs to shift towards monetization and profit models [3] - The total capital expenditure growth rate for the five major North American CSPs (Google, AWS, Meta, Microsoft, Oracle) is projected to reach 40% in 2026, driven by large-scale infrastructure investments and the replacement of general servers purchased during the 2019-2021 cloud investment boom [3] Group 2: AI Server Market Dynamics - The 2026 AI server market will be primarily driven by North American CSPs, government sovereign cloud projects, and large CSPs accelerating their own ASIC development and edge AI inference solutions [4] - GPUs are expected to account for 69.7% of AI chip usage, with NVIDIA's GB300 models becoming the mainstream for shipments, while VR200 will gradually ramp up in the second half of the year [4] Group 3: ASIC Development - The share of ASIC AI servers in shipments is expected to rise to 27.8% by 2026, the highest since 2023, with growth rates surpassing those of GPU AI servers [6] - Google is leading the investment in self-developed ASICs, with its TPU not only serving Google Cloud Platform infrastructure but also being sold to external companies like Anthropic [6]

Core Insights - The article highlights the significant growth in the AI server market, driven by increased investments from North American Cloud Service Providers (CSPs) and the rising demand for AI infrastructure, predicting a global AI server shipment growth of over 28% in 2026 [2][5]. Group 1: Market Growth Projections - Global server shipments are expected to grow by 12.8% in 2026, with AI server shipments contributing to this growth at over 28% [5][6]. - Major CSPs like Google and Microsoft are anticipated to increase their procurement of general servers to meet the rising demand for inference traffic [5][7]. Group 2: Technological Developments - The server market from 2024 to 2025 will focus on training advanced large language models (LLMs) using AI servers equipped with GPUs and HBM for parallel computing [6]. - By the second half of 2025, the development of AI inference services will accelerate, with CSPs shifting towards monetization and profit models [6]. Group 3: Capital Expenditure Trends - The total capital expenditure of major North American CSPs, including Google, AWS, Meta, Microsoft, and Oracle, is projected to increase by 40% in 2026, driven by large-scale infrastructure investments and the replacement of older general servers [7]. - Google and Microsoft are expected to be the most aggressive in increasing their general server procurement to support daily inference traffic demands [7]. Group 4: AI Server Market Dynamics - The AI server market in 2026 will be primarily driven by North American CSPs, government sovereign cloud projects, and the acceleration of ASIC development by large CSPs [8]. - GPU is expected to account for 69.7% of AI chip usage, with NVIDIA's GB300 models becoming the mainstream shipment [8]. Group 5: ASIC Server Developments - The shipment share of ASIC AI servers is projected to rise to 27.8% in 2026, marking the highest level since 2023, with growth rates surpassing those of GPU AI servers [8]. - Google is expected to lead the ASIC market, with significant investments in self-developed ASICs for its cloud services and external sales [8].

[music] We're talking today about identity for AI agents and how we authorize uh agents, MCP servers and uh the Um, we launched a new product uh actually this week. So, uh, that made this presentation fun. [laughter] Uh, had a major release just a few days ago um, for several of these features and ging these.Um, um, additionally, I should probably preface by saying a lot of this workshop material has been repurposed and um, our our architect uh, Abbyek, he goes by nicknames Shrek. um kind of prepared a lot ...